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Published in: BMC Medical Informatics and Decision Making 1/2012

Open Access 01-12-2012 | Research article

Effectiveness of a novel and scalable clinical decision support intervention to improve venous thromboembolism prophylaxis: a quasi-experimental study

Authors: Craig A Umscheid, Asaf Hanish, Jesse Chittams, Mark G Weiner, Todd EH Hecht

Published in: BMC Medical Informatics and Decision Making | Issue 1/2012

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Abstract

Background

Venous thromboembolism (VTE) causes morbidity and mortality in hospitalized patients, and regulators and payors are encouraging the use of systems to prevent them. Here, we examine the effect of a computerized clinical decision support (CDS) intervention implemented across a multi-hospital academic health system on VTE prophylaxis and events.

Methods

The study included 223,062 inpatients admitted between April 2007 and May 2010, and used administrative and clinical data. The intervention was integrated into a commercial electronic health record (EHR) in an admission orderset used for all admissions. Three time periods were examined: baseline (period 1), and the time after implementation of the first CDS intervention (period 2) and a second iteration (period 3). Providers were prompted to accept or decline prophylaxis based on patient risk. Time series analyses examined the impact of the intervention on VTE prophylaxis during time periods two and three compared to baseline, and a simple pre-post design examined impact on VTE events and bleeds secondary to anticoagulation. VTE prophylaxis and events were also examined in a prespecified surgical subset of our population meeting the public reporting criteria defined by the Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicator (PSI).

Results

Unadjusted analyses suggested that “recommended”, “any”, and “pharmacologic” prophylaxis increased from baseline to the last study period (27.1% to 51.9%, 56.7% to 78.1%, and 42.0% to 54.4% respectively; p < 0.01 for all comparisons). Results were significant across all hospitals and the health system overall. Interrupted time series analyses suggested that our intervention increased the use of “recommended” and “any” prophylaxis by 7.9% and 9.6% respectively from baseline to time period 2 (p < 0.01 for both comparisons); and 6.6% and 9.6% respectively from baseline to the combined time periods 2 and 3 (p < 0.01 for both comparisons). There were no significant changes in “pharmacologic” prophylaxis in the adjusted model. The overall percent of patients with VTE increased from baseline to the last study period (2.0% to 2.2%; p = 0.03), but an analysis excluding patients with VTE “present on admission” (POA) demonstrated no difference in events (1.3% to 1.3%; p = 0.80). Overall bleeds did not significantly change. An analysis examining VTE prophylaxis and events in a surgical subset of patients defined by the AHRQ PSI demonstrated increased “recommended”, “any”, and “pharmacologic” prophylaxis from baseline to the last study period (32.3% to 60.0%, 62.8% to 85.7%, and 47.9% to 63.3% respectively; p < 0.01 for all comparisons) as well as reduced VTE events (2.2% to 1.7%; p < 0.01).

Conclusions

The CDS intervention was associated with an increase in “recommended” and “any” VTE prophylaxis across the multi-hospital academic health system. The intervention was also associated with increased VTE rates in the overall study population, but a subanalysis using only admissions with appropriate POA documentation suggested no change in VTE rates, and a prespecified analysis of a surgical subset of our sample as defined by the AHRQ PSI for public reporting purposes suggested reduced VTE. This intervention was created in a commonly used commercial EHR and is scalable across institutions with similar systems.
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Metadata
Title
Effectiveness of a novel and scalable clinical decision support intervention to improve venous thromboembolism prophylaxis: a quasi-experimental study
Authors
Craig A Umscheid
Asaf Hanish
Jesse Chittams
Mark G Weiner
Todd EH Hecht
Publication date
01-12-2012
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2012
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/1472-6947-12-92

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